System and method to design structure for delivering electrical energy to tissue

ABSTRACT

A computer-assisted method can include defining a target volume of tissue activation to achieve a desired therapeutic effect for an identified anatomic region. At least one parameter can be computed for an electrode design as a function of the defined target volume of tissue activation. The computed at least one parameter can be stored in memory for the electrode design, which parameter can be utilized to construct an electrode.

RELATED APPLICATIONS

This application is a continuation-in-part of U.S. patent applicationSer. No. 10/885,982, which was filed Jul. 7, 2004, now U.S. Pat. No.7,346,382 and entitled Brain Stimulation Models, Systems, and Methods,and claims the benefit of provisional patent application No. 60/740,031which was filed on Nov. 28, 2005, and entitled “Role of electrode designon the volume of tissue activated during deep brain stimulation” theentire contents of both applications are incorporated herein byreference.

BACKGROUND

Electrical stimulation of the nervous system has provided a therapeutictreatment for a variety of disorders. For example, electricalstimulation has been applied to pain management, such as by performingstimulation of the spinal cord. Electrical stimulation has also beenperformed to augment hearing in the context of cochlear implants. Deepbrain stimulation (DBS) has become an established therapy for treatingvarious conditions including, for example, Parkinson's disease anddystonia. DBS has also been employed to treat several other conditions,such as clinical depression, obsessive compulsive disorder, and epilepsyto name a few.

By way of further example, the discovery that high frequency DBSgenerates clinical benefits analogous to those achieved by surgicallesioning has transformed the use of functional neurosurgery for thetreatment of movement disorders. In first world countries, thalamic DBSfor intractable tremor has replaced ablative lesions of the thalamus,and DBS of the subthalamic nucleus or globus pallidus intemus (GPi). GPihas replaced pallidotomy in the treatment of the cardinal motor featuresof Parkinson's disease (e.g., tremor, rigidity, bradykinesia). Inaddition, GPi DBS has emerged as an effective therapy for dystonia, andthe utility of DBS is being examined for the treatment of epilepsy,obsessive-compulsive disorder, Tourette's syndrome, and majordepression.

Despite the documented clinical successes of neurostimulation, themechanisms and effects of neurostimulation at the neuronal level remaindifficult to predict. As a result, modeling and simulation have playedincreasingly important roles in the engineering design and scientificanalysis of neurostimulation.

SUMMARY

The present invention relates systems and methods for designing anelectrode to provide for stimulation of an anatomical region to achievea desired therapeutic effect. According to an aspect of the invention,systems and methods can be employed to determine an electrode designthat is customized to the anatomical and/or morphological features of anidentified stimulation target. For instance, the systems and methods canbe employed according to an aspect of the invention to determineelectrode design parameters, which can include one or more of structuralparameters (e.g., electrode height, diameter, and/or shape) andelectrical parameters (e.g., voltage or current amplitude, frequency,pulse width or duration, and/or waveform shape).

One aspect of the invention provides a computer-assisted method thatincludes defining a target volume of tissue activation to achieve adesired therapeutic effect for an identified anatomic region. At leastone parameter is computed for an electrode design as a function of thedefined target volume of tissue activation. The computed parameter(s)can be stored in memory for the electrode design. The one or moreparameters can be used to construct a custom electrode for treatment ofa given disorder.

Another aspect of the invention provides a method for determining anelectrode design. The method can include selecting an anatomical regionto achieve a desired therapeutic effect and defining a target volume oftissue activation in the selected anatomical region expected to achievethe desired therapeutic effect. At least one electrode structureparameter and at least one stimulation parameter are determined toprovide a design volume of tissue activation that substantially matchesthe target volume of tissue activation. The determined at least oneelectrode structure parameter and the at least one stimulation parametercan be stored, such as to define the electrode design.

Still another aspect of the invention provides a system to determine anelectrode design. The system includes memory that stores data defining atarget volume of tissue activation in an anatomical region expected toachieve a desired therapeutic effect. An optimization method determinesa value of at least one electrode design parameter, which defines theelectrode design, expected to provide a design volume of tissueactivation that substantially matches the target volume of tissueactivation.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an example of a system that can be utilized to design anelectrode according to an aspect of the invention.

FIG. 2 depicts a schematic example of an electrode that can beconstructed from an electrode design according to an aspect of theinvention.

FIG. 3 is a flow diagram of a general method that can be employed todesign an electrode according to an aspect of the present invention.

FIG. 4 depicts a functional block diagram of an example approach thatcan be employed to determine a volume of tissue activation according toan aspect of the invention.

FIG. 5 depicts a graph plotting thresholds that can be applied topredict neural stimulation.

FIG. 6 depicts a plot of a second difference-based approach that can beused to predict neural stimulation.

FIG. 7 depicts an example of a volume of tissue activation that can beascertained for an isotropic tissue medium.

FIG. 8 depicts an example of a volume of tissue activation that can beascertained for an anisotropic and inhomogeneous tissue medium.

FIG. 9 depicts an example of a design system that can be implementedaccording to an aspect of the invention.

FIG. 10 depicts an example image of a target VTA that can be used fordesigning an electrode according to an aspect of the invention.

FIG. 11 depicts an example of a first design VTA overlayed on the imageof FIG. 10.

FIG. 12 depicts an example of a second design VTA overlayed on the imageof FIG. 10.

FIG. 13 depicts an example of a third design VTA overlayed on the imageof FIG. 10.

FIG. 14A depicts examples of contour plots for second differencethreshold values for a first electrode design at different stimulationparameters that can be used for designing an electrode according to anaspect of the invention.

FIG. 14B depicts examples of contour plots for second differencethreshold values for a second electrode design at different stimulationparameters that can be used for designing an electrode according to anaspect of the invention.

FIG. 14C depicts examples of contour plots for second differencethreshold values for a third electrode design at different stimulationparameters that can be used for designing an electrode according to anaspect of the invention.

FIG. 15 depicts a graph of electrode dimensions plotted as a function ofVTA aspect ratios for example design parameters.

FIG. 16 depicts a graph of VTA volume plotted as a function of electrodeheight for example design parameters.

FIG. 17 depicts a graph of VTA volume plotted as a function of electrodediameter for example design parameters.

FIG. 18 depicts an image representing an example target VTA in thethalamus.

FIG. 19 depicts an image representing an example design VTA superimposedon the target VTA of FIG. 18 for a first electrode design.

FIG. 20 depicts an image representing an example design VTA superimposedon the target VTA of FIG. 18 for a second electrode design.

DETAILED DESCRIPTION

The present invention relates to systems and methods that can beemployed to ascertain an electrode design to achieve a target volume oftissue activation in an anatomical region (e.g., a nucleus) that isidentified with a desired therapeutic effect. The anatomical region andtarget volume of tissue activation can vary according to the particulardisorder being treated as well as the anatomic features of such region.

As one example, a common electrode design is currently used in mostexisting DBS applications, even though substantial morphological andanatomical differences exist between the various target nuclei in thebrain. Differences can become more pronounced for neurostimulationapplied to other anatomical structures, such as the spinal cord orperipheral nerves. Accordingly, the systems and methods described hereinallow the design of one or more electrode parameters that can beemployed to construct an electrode capable of achieving improvedperformance relative to many existing electrodes. For example, such anelectrode can be customized for use in providing electrical stimulationto a desired anatomical site, such as a nucleus, identified fortreatment of a particular disorder. Additionally or alternatively, theelectrode design can be further customized for stimulating a targetanatomical volume for a given patient.

Referring to FIG. 1, an example of a basic system 10 for determining anelectrode design is illustrated. The system 10 is depicted as beingimplemented using a computer 12 that is programmed and/or configured todetermine one or more electrode design parameters 14 according to anaspect of the invention. The computer 12 can be a workstation, astandalone computer, a notebook computer, or it can be implemented aspart of a microprocessor-based appliance or other equipment availablethat is programmed based on the teachings contained herein.

The computer 12 includes a processor 16 that is operative to executeinstructions for performing the methods described herein. Theinstructions can be stored in associated memory 18. In the example ofFIG. 1, the processor 16 is depicted as running a design algorithm 20.Such design algorithm 20 can be stored in the memory 18 and loaded intothe processor 16 for determining the electrode design. The designalgorithm 20 can be programmed to determine one or more electrode designparameters 14 as a function of a target volume of tissue activation(VTA), as defined by VTA data 22.

As used herein, the target VTA represents an anatomical region in whichneurons within such region are expected to be activated to achieve adesired therapeutic effect. Stated differently, the neurons within theVTA are expected to generate propagating action potentials at a stimulusfrequency in response to electrical stimulation delivered at astimulation electrode contact located within the VTA. While the phrase“volume of tissue activation” and its equivalents typically represents avolume of tissue activation of an anatomical region, it will beappreciated that such volume could also represent a volume of inhibitionregion or a volume of tissue deactivation, as the stimulation couldresult in either generation of an activation potential or the inhibitionof existing activation potential.

The target VTA thus can be predefined for a given patient or a set ofpatients, such as for treating an identified disorder, and stored as theVTA data 22. Alternatively, the target VTA can be pre-computed for oneor more known anatomical regions, which VTA can be warped or morphed tofit the corresponding anatomical region of a particular patient andstored to provide the target VTA data 20. As another alternative, atarget VTA can be computed by the computer 10 (or another computer—notshown) and stored as the VTA data 20. Some example approaches that canbe employed to determine the target VTA are described herein (see, e.g.,FIG. 4). As one example, the target VTA can correspond to aprobabilistic definition of the anatomical volume in an identifiedanatomical region derived from clinical tests performed on astatistically significant population. These and other examples of how aVTA and, in particular, a target VTA can be determined are described inthe above-incorporated U.S. patent application Ser. No. 10/885,982.Those skilled in the art will understand and appreciate other ways inwhich the VTA data 22 can be generated and stored for use by the system10.

The electrode design parameters 14 computed by the design algorithm 20can include electrode structural (or morphological) parameters 24,electrode stimulation parameters 26 or a combination of structural andstimulation parameters. For the example of an electrode having acylindrical electrode contact, the electrode structural parameters 24can include the height and/or diameter of each cylindrical electrodecontact. For an electrode having one or more contacts that are spacedapart from each other along the electrode shaft, the structuralparameters 24 can also include an axial spacing between electrode pairs.It will be understood and appreciated that the electrode contacts canhave other shapes than a circular cylindrical shape. For example, anelectrode contacts can have a substantially C-shaped cross-section, suchthat the electrode structural parameters 24 can include the radius ofcurvature, the arc length, and/or an axial length of the contact. Thus,the arc length thus can range from zero degrees (corresponding to nocontact) up to 360 degrees (corresponding to a cylindrical type ofcontact). The electrode structural parameters 24 can include othergeometric features (e.g., shape, contours, discontinuities, and thelike) and interrelationships for the contacts that form the electrode.

The electrode stimulation parameters 26 can also be determined by thedesign algorithm 20 to achieve a desired therapeutic effect by providingelectrical stimulation to a target VTA.

Those skilled in the art will understand and appreciate variousoptimization methods that can be utilized by the design algorithm 20 todetermine the structural parameters and/or the electrical parameters forthe electrode design for approximating the target VTA. For example, insome cases it may be sufficient to ascertain the structural parameter(s)24 over a predefined set of stimulation parameters 26 during a firstoptimization routine. The stimulation parameters 26 can be fine tunedduring a second optimization routine. Alternatively, the structuralparameters 24 and the electrical parameters 26 can form a parameterspace that is optimized collectively. The order and interrelationshipbetween the stimulation parameters and the structural parameters thuscan be optimized to achieve or approximate a desired therapeutic effectto varying degrees of specificity and according to what approximationsand assumptions are made during such analysis. Additionally, theresulting parameters 14 can be determined to accommodate anatomicalvariability between patients as well as potential surgical variabilityassociated with implantation of the electrode to a target implantationsite. The electrode design parameters 24 further can be ascertained toprovide electrode contact dimensions that maximize the stimulationinfluence while keeping charge injection levels to a minimum.

The system 10 can also include a display 30 that can be utilized torepresent the results and calculations performed by the designalgorithm. For instance, the display can demonstrate a graphicalrepresentation, textual representation or a combination graphical andtextual information associated with determining an electrode design. Asone example, a graphical interface can provide data to the display 30for overlaying an expected VTA for one or more given designs over thetarget VTA. Such a representation provides a visual demonstration ofexpected performance that can help determine which design parametersshould be utilized to construct an electrode for given situation.

The system 10 can also include one or more other input or output devices32. Such devices 32 can provide an interface through which a user caninput data as well as control the design algorithm 20. For example, auser can employ the I/O device 32 to input data, such as instructions toinitiate or modify the electrode design procedure. Alternatively, theI/O device can be employed to acquire the VTA data 22, such as fromanother location in the memory 18, from another storage location, or toacquire the VTA data from another process running on the computer 12 onanother machine. A user can also employ the I/O device 32 to set therange of parameters 14, the granularity of such parameters as well as toprogram other parameters being used in the procedure. The I/O device 32can also be utilized to interface and enable acquisition of data (e.g.,imaging data) from an associated imaging device, such as a magneticresonance imaging (MRI) system, a computer tomography (CT) system orother imaging modality.

As another example, the I/O device 32 can correspond to an implantablepulse generator (or other stimulation equipment). The computer 18 canprogram the I/O device 32 based on the stimulation parameters 26determined to achieve maximal VTA coverage relative to the target VTAfor the electrode design. In this way, a custom-designed electrode(constructed according to the electrode structural parameters 24) can beoperated with appropriate stimulation parameters, to achieve stimulationthat substantially matches the target VTA. It will be understood andappreciated that the system 10 thus can be employed to determine anelectrode design (e.g., including structural and electrical stimulationparameters) that can achieve a VTA with increased specificity. Thus, thesystems and methods described herein will facilitate more accurateneurostimulation.

FIG. 2 depicts a schematic example of part of an electrode 40 that canbe constructed based on design parameters determined according to anaspect of the invention. The electrode 40 can include one or morecontacts 42 that are spaced axially apart from each other along anelongated shaft 44 of the electrode. In the example of FIG. 2, each ofthe contacts 42 is depicted as a cylinder having a height (H) and adiameter (D), such as can be determined as part of an electrode designaccording to an aspect of the invention. The relationship between heightand diameter can be characterized as an aspect ratio (d/h), which itselfcan also be a design parameter. It will be understood that the electrodecontacts 42 can have the same diameter and height or the diameter andheight can vary among the contacts. Thus, various combinations existthat can provide for the same or different surface area for each of thecontacts 42.

As shown in the enlarged portion of the electrode 40, the height of theelectrode contact 42 is defined by the distance between axially spacedapart edges 44 and 46. While the edges are depicted as being annularedges, other shapes (e.g., sinusoidal, saw tooth, and the like) can alsobe provided at the respective edges 44 and 46. Each contact also has adiameter, which is fixed for a substantially right-circular cylindricalelectrode configuration. Other shapes and configurations could also beutilized, which may or may not be cylindrical. As mentioned above, theelectrode design algorithm 20 (FIG. 1) can also determine the spacing 48between adjacent pairs of the electrode contacts 42. The spacing 48between the adjacent pairs of the electrode contacts 42 can be differentor it can be the same. Thus, the structural parameters of the electrode40 can vary depending on the dimensions and configuration of the targetVTA for the intended target location of the electrode. While the exampleof FIG. 2 has been described in the context of plural cylindricalelectrode contacts, it will be understood that, as described herein, thesystems and methods of the present invention are not limited to anyparticular electrode geometry. Instead, the approach described hereinallows for any shape and configuration and dimension of electrodecontact(s) to be deigned for providing electrical stimulation that canachieve a target VTA for achieving a desired therapeutic effect.

A general method 50 that can be employed to determine an electrodedesign according to an aspect of the invention is depicted in FIG. 3.The method includes defining a target VTA, indicated at 52. As describedherein, the target VTA can be defined by pre-computing a VTA fortreatment of a particular disorder, such as can be based on dataacquired for one or more patients, or for a given patient according tosuch patient's condition. At 54, one or more electrode design parametersare computed. The electrode design parameters can include structuralparameters, electrical parameters or a combination of structural andelectrical parameters. The method 50, as well as variations thereof, canbe implemented by a computer programmed accordingly. The method 50 canbe performed automatically or portions of the method can which caninclude selection and acts performed by one or more persons. The method50, as well as variations thereof, can also be embodied in acomputer-readable medium, such as can be stored in memory of a computeror computer appliance, or be stored on an article of manufacture.Variations of this method 50 will be better appreciated with referenceto other parts and embodiments provided in this description, includingwith respect to FIG. 1 and the following other FIGS. 4-20.

FIG. 4 depicts an example of a function block diagram of a system 100that can be employed to determine a VTA 102 according to an aspect ofthe present invention. The system 100 can be implemented on a computeror workstation programmed to perform the methods and functionsrepresented in and described with respect to FIG. 4. The system 100further can be performed to calculate a target VTA 104 for achieving adesired therapeutic effect. For instance the target VTA 104 defines ananatomic region for stimulation that is expected to achieve a desiredtherapeutic effect, such as by generating propagating action potentialsin response to electrical stimulation by one or more electrode contactslocated within or near the target VTA. As described herein, the targetVTA 104 can be utilized to compute one or more electrode geometryparameters (e.g., height, diameter, contact spacing, shape) andstimulation parameters (voltage or current, frequency, pulse width, andwaveform shape) for an electrode design.

The system 100 of FIG. 4 includes a finite element model (FEM) solver106 that is programmed and/or configured to determine a spatial andtemporal voltage solution 112 based on anatomical and electrical models108 and 110, respectively. The spatial and temporal voltage solution 112can also vary according to stimulation parameters 114. For example, theFEM solver 106 can determine a spatial and temporal voltage solution 112for each (or a subset) of the available stimulation parameters 114 basedon the models 108 and 110.

The anatomical model 108 defines the location of the electrode as wellas structural features of the anatomical region being modeled for use inthe system 100. The anatomical model 108 can be generated using asuitable imaging modality (e.g., MRI or CT imaging), which can beutilized to define the electrode location in the anatomical region andthe surrounding anatomical structures. For instance, the preliminaryinitial contact location can be at the anatomic center of the nucleus.The anatomical model 108 is coupled to the electrical model 110 thatcharacterizes the electric field generated in the anatomical region. Theelectrical model 110, for example, can characterize tissue conductivityin the anatomical region of interest. As one example, the electricalmodel 110 can represent the tissue conductivity of the region as beingisotropic and homogeneous. As another example the electrical model 110can characterize the tissue conductivity as being anisotropic andinhomogeneous. The particular characterization can vary according to thedesired accuracy and the particular type of tissue being represented bythe anatomical and electrical models. The electrical model 110 can alsocharacterize the electrical properties of the tissue electrode interfaceas well as the electrode impedance and the electrode capacitance. Theelectrical model 110 further can reflect the time dependencecharacteristics at the electrode tissue interface (e.g., via FourierFEM), such as due to the electrode capacitance.

By way of example, many electrodes (e.g., as used for DBS) arethree-dimensional structures and the tissue conductivity of the centralnervous system is both inhomogeneous (dependent on location) andanisotropic (dependent on direction). The tissue inhomogeneity andanisotropy surrounding the electrode can alter the shape of the electricfield and the subsequent neural response to stimulation. The anisotropyand inhomogeneity of such tissue medium can be accounted for by the FEMsolver 106 and the electrical model 110 incorporating 3D tissueconductivities of the tissue. As one example, diffusion tensor imaging(DTI) can be employed to estimate an electrical conductivity tensor ofthe tissue medium surrounding one or more electrodes.

For instance, diffusion tensor imaging (DTI) can be employed tocharacterize the diffusional behavior of water in tissue on avoxel-by-voxel basis in terms of a matrix quantity from which thediffusion coefficient can be obtained corresponding to any direction inspace. The electrical conductivity tensor (σ) of a tissue medium isobtainable from the corresponding diffusion tensor (D) determined forthe tissue medium. The hypothesized relationship between electricalconductivity and water diffusion in tissue is prompted by theobservation that in a structured medium the two processes are relatedthrough mutual respect for the boundary conditions imposed by the tissuegeometry. It has been determined that a value of the electricalconductivity tensor a can be obtained for each voxel (e.g., from DTIdata) using a linear transform of the matrix D:σ=(σ_(e) /d _(e))D  Equation 1

-   -   where σ_(e) is the effective extracellular conductivity, and    -   d_(e) is the effective extracellular diffusivity.        The diffusion tensors obtained from a corresponding DTI modality        can be transformed to conductivity tensors, as discussed above,        and incorporated into the electrical model 110 and the FEM        solver 106.

The FEM solver 106 thus can solve for the spatial and temporal voltagedistribution (e.g., a potential distribution (V_(e))) 112 that isgenerated in the tissue medium in response to electrical stimulation inthe tissue according to the stimulation parameters 114. The unit ofpotential distribution can correspond to a single voxel, which canrepresent a pixel or a set of plural. For example, the FEM 106 solvercan determine the potential distribution 112 in the anatomical region oftissue, which can vary according to the tissue model utilized by the FEMsolver 106. The potential distribution 112 thus can represent theelectric field for each voxel for predefined electrode contact geometryand stimulation parameters. As one example, the FEM solver 106 can beimplemented as a Fourier FEM solver that accounts for the capacitance ofthe electrode-tissue interface under voltage-controlled stimulation. TheFEM solver thus can incorporate the DTI-based tissue conductivities andthe reactive components of the electrode-tissue interface into a singlesystem of equations.

One or more thresholds 116 can be applied to the potential distribution112 to ascertain (or predict) whether an activation potential has beenachieved for each given unit (e.g., voxel) of the potentialdistribution. The thresholds 116 can be predefined and applied to thepotential distribution 112 to determine a corresponding VTA 102according to whether a corresponding activating potential has beenachieved for each voxel. The VTA 102 can be computed for a defined setof stimulation parameters 114, such that a plurality of VTAs 102 can bedetermined to define a corresponding search space. The system 100 canrecompute the VTA 102 (and appropriate intermediate values) for each setof stimulation parameters, which procedure is schematically representedby connection 118. That is, a corresponding search space of VTAs 102 canbe determined over a range of stimulation parameters 114. The resultingsearch space of VTAs 102 can be analyzed by an optimization method 120to ascertain the target VTA 104.

The thresholds 116 can be implemented by employing a neurostimulationpredictor that ascertains whether a corresponding activating potentialhas been reached for. As one example, a Fourier FEM DBS electrode modelcan be coupled to an axon or neuron model (e.g., a field-neuron model)for the anatomical region to determine whether an activation potentialexists for each voxel. Appropriate thresholds 116 can be defined for theaxon or neuron model sufficient to trigger an activating potential inthe aggregate FEM analysis.

An alternative approach to the field-neuron simulations described aboveis the use of an activating function-based technique. One example ofsuch an activating function that can be employed to approximate theneuron response to electrical stimulation is a second difference of theextracellular potential distribution along a neural process (∂²Ve/∂x²),where V_(e) represents the potential of a given voxel. The seconddifference provides a quantitative estimate of the polarization of theaxon or neuron in response to an applied electric field. The seconddifference thus can be applied to the potential distribution to define3D surfaces that encompass the volume, where ∂²Ve/∂x² is suprathresholdfor axonal activation for the given stimulation parameters 114.

By way of illustration, FIG. 5 depicts a graph that includes an exampleof ∂²Ve/∂x² function that can be utilized as a predictor of neuralactivation. In the example of FIG. 5, the ∂²Ve/∂x² values are plotted asa function of electrode-axon distance measured from the center of theelectrode. An absolute threshold (indicated by a dashed line 142) is onetype of simple predictor that can provide a low level of accuracy inpredicting neural activation. An alternative approach is to perform acurve fitting function to provide a corresponding variable threshold(indicated by solid line 144) that approximates clinical raw data.

Yet another alternative approach is to determine the ∂²Ve/∂x² thresholdvalues as a function of pulse width and voltage. Specifically, ∂²Ve/∂x²threshold values are recorded, and these values are expressed as afunction of cathodic voltage (V) times pulse width (PW, μs). Thisexpression allows two stimulation parameters to be condensed into asingle number for prediction of thresholds. Further, threshold valuesrecorded this way were found to be valid for a wide range of electrodedesigns and stimulation parameters. These values can then be used tocreate 2D spatial contours that are swept around the z-axis to definethe VTA volume. For purposes of volume calculations, it is oftenconvenient to describe the VTA contours with analytical functions. Forexample, each contour can be described by an ellipse:(x−x0)² /a2+(y−y0)² /b2=1  Equation 2

-   -   where x0, y0 is the center of the ellipse, and    -   a and b are the semimajor and semiminor axes, respectively        (assuming b<a).        The semimajor and semiminor coefficients are calculated from the        following: a=distance of threshold value from electrode contact        along x-axis; b=maximum y value of 2D threshold contour. Under        the model conditions used in this study, the electrode contact        is centered on the origin and the center of each ellipse is        x0=a, y0=0. With this method, ∂²Ve/∂x² threshold values and VTA        volumes can be predicted for a wide range of electrode designs        and stimulation parameters.

FIG. 6 depicts an example of spatial ellipsoid-based predictors 148 thatcan be implemented as described above. The predictors 148 can be appliedto a variety of electrode design and stimulation parameters. In theexample of FIG. 6, corresponding ∂²Ve/∂x² predictors forvoltage-controlled stimulation are overlaid on filled ∂²Ve/∂x² thresholdcontours, as represented by the associated indicator bar located to theright of the figure. The ∂²Ve/∂x² threshold contours can be generatedfrom the integrated field neuron model, as described herein.

By way of further example, FIGS. 7 and 8 depict example images 150 and152, respectively, demonstrating different VTAs that can be determinedfor deep brain stimulation by applying different tissue models for thesame activating function. For sake of consistency, similar referencecharacters refer to the same structural and anatomical parts in each ofthe FIGS. 7 and 8.

In FIG. 7, the VTA, indicated at 154, is determined for a tissue modelwhere the tissue medium is represented as being isotropic andhomogeneous. In FIG. 8, the image 152 demonstrates the VTA, indicated at156 for a model that represents the tissue medium as being inhomogeneousand anisotropic (a more complex and usually more accurate tissuerepresentation), such as a DTI-based tissue medium. A comparison of theapproaches demonstrates the resulting differential activation ofsurrounding anatomical structures.

Each of the tissue models utilized to derive the images of FIGS. 7 and 8includes a tissue encapsulation layer 160 around the electrode shaft162. The electrode shaft 162 extends through the thalamus 164 andterminates with its distal end located within or adjacent thesubthalamic nucleus (STN) 166. A plurality of electrode contacts 168 aredisposed in a spaced apart relationship along the length of the shaft162. The VTA 154 corresponds to a volume of tissue within a boundarydefined by activating function applied for a given set of stimulationparameters one of the contacts 168 within the STN 166. In FIG. 8, theVTA 156 similarly corresponds to a volume of tissue within a boundarydefined by activating function applied for the same given set ofstimulation parameters at a single contact within the STN 166. The VTA154 (FIG. 7) and the VTA 156 (FIG. 8) generated under the two conditionswere matched for electrode impedance.

Referring back to FIG. 4, the system 100 also includes a VTA evaluationblock 120 that is operative to search through the VTAs to determine thetarget VTA 104 for achieving a desired therapeutic effect. Theevaluation block 120 can be implemented as a computer-implemented (orcomputer-assisted) algorithm that evaluates the candidate VTAs 102 inthe search space. The evaluation block, for example, can include ascoring function 122 that assigns a score to each candidate 120 VTA. Thescore can help a user select the target VTA from the VTA search space.Alternatively, the evaluation block 120 can automatically select thetarget VTA based, at least in part, on the score provided for each VTA102 in the search space. The VTAs and their scores can be displayed to auser, such as by providing corresponding data to a display or otheroutput device (e.g., a printer).

As one example, the evaluation algorithm of the evaluation block 120 canemploy one or more criteria that establishes: (a) one or more regions inwhich activation is desired; or (b) one or more regions in whichactivation should be avoided. For example, the scoring function 122 candetermine a score of how each candidate VTA maps against desired andundesired regions. In one example, the scoring function computes thescore as a function of the number of VTA voxels that map to the one ormore regions in which activation is desired, and the number of VTAvoxels map to the one or more regions in which activation is undesired.As another example, these two quantities may be weighted differentlysuch as, for instance, if avoiding activation of certain regions is moreimportant than obtaining activation of other regions (or vice-versa). Inyet another example, these two quantities may be used as separatescores. As another example, the evaluation block 120 and scoringfunction 122 can be implemented based on documented therapeutic effectand assign a corresponding raw score to each VTA and its associatedstimulation parameters.

By way of further example, for the example of employing the system 100to determine a target VTA for treatment of Parkinson's disease, the rawscore provided by the scoring function 122 can correspond to documentedimprovement according to blinded Unified Parkinson's Disease RatingScale (UTPDRS) evaluation. The VTAs can also be designated with one ormore primary symptoms of improvement, such as rigidity, bradykinesia,and/or tremor. The VTA can also be designated as being non-therapeuticwhen a given VTA is identified with a clinically defined side effecttype (e.g., muscle contraction, parasthesia, and the like). Thedesignation symptomatic relief and side effects can also be weighted andapplied to scoring criteria according to the perceived conditions (e.g.,through clinical testing) associated with a given VTA. Other scoringcriteria can exist for Parkinson's disease as well as for other types ofdisorders that can be utilized by the evaluation block 120. The scoringfunction 122 thus can provide an indication of the therapeutic andnon-therapeutic effect associated with the VTAs 102.

A 3D probabilistic map or functional VTA atlas can also be generatedfrom the VTA data 102, which that can further be utilized to determinethe target VTA 104. The VTA data, for example, can be acquired forplurality (e.g., hundreds or thousands) of patients so that VTA 102 foreach patient can provide quantitative relationship between the VTA and adesired therapeutic effect for the patients. For example, each of theVTAs 102 can be broken up into a voxelized grid in which each voxelretains the score determined for the respective VTA. The voxel matrixcan be statistically analyzed to provide a corresponding probabilityvalue for each voxel in the matrix that represents a statistical scorefor each voxel in the functional atlas. With a sufficiently large searchspace, a corresponding target VTA thus can be identified based on theaggregate set of VTAs 102 in the search space. Side effect pathways canalso be integrated into the 3D probabilistic map of therapeutic VTAs asareas to avoid when defining the target VTA 104. The resultingprobabilistic VTA map can be utilized to determine the target VTA basedon imaging data for a given patient. Those skilled in the art willunderstand various other approaches that can be employed to determinethe target VTA from a given search space of VTAs based on the teachingscontained herein. For example, the target VTA can also be user defined,such as based on clinical testing or empirical testing or a combinationof clinical and empirical testing.

FIG. 9 depicts an example of an electrode design system 200 that can beimplemented according to an aspect of the invention. The system 200 canbe implemented as computer-executable instructions running in one ormore computers or other processor-based systems. The system 200 includesa parameterization space 202 that includes parameters that represent oneor more design parameters that can be varied to provide an electrodedesign 204 for achieving a desired therapeutic effect. The purpose ofthe system 200 is to determine which parameter or combination of pluraldesign parameters can best match a target volume of tissue activation(VTA) 206. One or more of the parameters for the electrode design oravailable ranges can be established by a user input, for example.

The target VTA 206 defines a region of tissue that, if stimulated by anelectric field from the electrode located therein, generates an actionpotential that has been determined to achieve a desired therapeuticeffect. The therapeutic effect and the location of the target VTA 206can vary according to the disorder of a particular patient. The targetVTA 206 can be predetermined for a given patient, such as based onsimulation, clinical testing or a combination of simulation and clinicaltesting (e.g., see FIG. 4 and the corresponding description).Alternatively, the target VTA 206 can be computed by the system 200 inconjunction with the determination of the electrode design 204. The VTAfor a given electrode design varies as a function of geometry (e.g.,height, diameter, and spacing) of the individual cylindrical electrodecontacts of the electrode.

As an example, FIG. 10 depicts an image 300 that includes arepresentation of a target VTA 302 that can be utilized to determine theelectrode design for a given target nucleus. As shown in FIG. 10, anelectrode 304 includes a plurality of contacts 306, at least one ofwhich is located in the target VTA 302. The electrode shaft extendsthrough the thalamus 308 and through at least a portion of the STN 310.In the example of FIG. 10, the target VTA 302 encompasses the dorsal STNand ZI/H2, such as represents a preliminary definition of a target VTAfor STN DBS. Those skilled in the art will appreciate that the designsystem 200 (FIG. 9) is applicable to determining target VTAs for othernuclei in the brain as well as in other anatomical regions.

Referring back to FIG. 9, the parameterization space 202 includes arange of electrode structure parameters 208. For the example of anelectrode having a plurality of cylindrical electrode contacts, theelectrode structure parameters 208 can include the height, diameter andspacing (or distribution) of the electrode contacts along the electrodeshaft. As an example, a predefined range of values for the height anddiameter parameters can be stored as part of the parameterization space(e.g., by setting limits for minimum and maximum height and diameters).Relationships between parameters can also be parameterized, such as theaspect ratio (d/h). The aspect ratio further can be utilized toconstrain the optimization procedure, such as by limiting the searchspace to a predefined range of aspect ratios (e.g., d/h<some predefinedvalue), which can be set according to the shape and size of the targetVTA 206.

The parameterization space 202 can also include electrode stimulationparameters 210, such as voltage or current amplitude, frequency, pulsewidth and pulse shape. The stimulation parameters can be applied to oneor more electrode contacts uniformly or different set stimulationparameters can be applied to each electrode contact independently of theother electrode contacts. The contact location and trajectory of theelectrode within an anatomical region can be included as parameters 212in the parameterization space 202 identifying relative electrode andcontact placement in an anatomical region. For example, the contactlocation can be centered in the anatomical region defined by the targetVTA 206 and the trajectory can be set to a corresponding standardtrajectory for the target nucleus. Alternatively, such parameters can bevaried, as described with respect to other example embodiments describedherein.

An optimization method 214 controls the parameter searching over theparameterization space 202. The optimization method 214 can evaluate adesign VTA 216 for an instance of the parameterization space 202relative to the target VTA 206 to ascertain which instance (or subset ofinstances) of the parameterization space provides a design VTA that bestmatches the target VTA. The optimization method 214 can include one ormore search algorithms programmed to determine the electrode design 204.

As one example, the optimization method 214 can include an electrodestructure search 218 that is programmed to search the parameterizationspace 202 to determine one or more instances of electrode structureparameters. For example, the electrode structure search 218 caninitialize the parameterization space 202 to set the electrode structureparameters 208 (height and diameter) to predetermined dimensions, suchas can be arbitrarily set or can be set based on various criteria (e.g.,empirical or clinical studies). The electrode location/trajectoryparameters 212 can remain fixed during application of the electrodestructure search 218. The electrical stimulation parameters 210 can bevaried for a given set of electrode structure parameters 208 to providemaximal design VTA coverage relative to the target VTA 206, as describedherein.

The system 200 includes an electrode field model 220 and a tissue model222 that are employed by a VTA predictor 224 to determine the design VTA216 for a given instance or over a set of plural instances of theparameterization space 202. The VTA predictor 224 predicts the neuralresponse to stimulation, corresponding to the design VTA 216, byapplying the potential distribution of the electrical field model 220 tothe neuron/axon model 222. The neural response to extracellularstimulation is dependent on several factors, such as, for example: (1)the electrode geometry (e.g., the electrode structure parameters 208);(2) the electrode stimulation parameters 210 (e.g., stimulus waveform,stimulation frequency, pulse width, etc.); (3) the shape of the electricfield (e.g., as determined by the inhomogeneous and anisotropic bulktissue properties); (4) the neuron geometry; (5) the neuron positionrelative to the stimulating electrode; and (σ) the neuron membranedynamics. Some or all these factors can be represented in the electricfield model 220 and the neuron/axon model 222.

As one example, the electric field model 220 can be implemented as acomputer-solvable FEM mesh based on the electrode structure parameters208 and the stimulation parameters 210 in the parameterization space202. The electric field model 220 thus can include a stimulatingelectrode model that represents the morphology (or structure) of theelectrode, as established by the electrode structure parameters 208employed by the electrode structure search 218. The electric field model220 can also include a representation of the conductivity of a thinlayer of tissue encapsulating the particular electrode, which providesthe electrode tissue interface. The electric field model 220 can alsoexplicitly represent the electrode impedance and the electrodecapacitance. The electric field model 220 also includes tissueconductivity model that represents the anatomical structure surroundingthe electrode. As described herein, the tissue conductivity model caninclude data that represents inhomogeneous or anisotropic properties ofthe tissue near the stimulation electrode, such as can be obtained byDTI imaging or by using other techniques described herein.Alternatively, the tissue conductivity model might include data thatrepresents tissue near the stimulation electrode as being homogeneousand isotropic, such as described herein. The electric field model 220thus represents a potential distribution in the tissue medium for agiven set of parameters (e.g., electrode structure and electrodestimulation parameters) in parameterization space 202.

The neuron/axon model 222 can include a multi-compartment neuron or axonmodel that positions the modeled neurons or axons at specifiablepositions along one or more nerve pathways in the FEM mesh defined bythe electric field model 220. In addition to properties of individualneurons, the neuron/axon model 222 may depend on one or more of theparameters (e.g., electrode structure parameters 208 and electricalstimulation parameters 210) of the stimulation being modeled. Forexample, the stimulation pulse width will affect the neuron response.Therefore, in one example, the neuron/axon model 222 can be tailored toa specific value for one or more DBS stimulation parameters. By way offurther example, the nerve pathways can be ascertained using DTI-derivedimaging data, or by using anatomic atlas data, or any other appropriatetechnique.

Those skilled in the art will understand appreciate various neuronmodels or axon modeling techniques that could be employed in the system200. An example of an axon model is described in Cameron C. McIntyre etal., “Modeling the Excitability of Mammalian Nerve Fibers: Influence ofAfterpotentials on the Recovery Cycle,” J. Neurophysiology, Vol. 87,February 2002, pp. 995-1006, which is incorporated by reference hereinin its entirety, including its disclosure of axon models. In anotherexample, a more generalized neuronal model can be used, an example ofwhich is described in Cameron C. McIntyre et al., “Cellular Effects ofDeep Brain Stimulation: Model-Based Analysis of Activation andInhibition,” J. Neurophysiology, Vol. 91, April 2004, pp. 1457-1469,which is incorporated by reference herein in its entirety. Theneuron/axon model 222 describes how the neurons will respond to anapplied electric field; namely whether the neuron will fire and whetherthe neurons will generate a propagating action potential.

As a further example, the neuron model 222 geometries are typicallybroken up into many (e.g., hundreds) of compartments. The VTA predictor224 can co-register the various compartments of the neuron/axon model222 within the FEM mesh of the electric field model 220. Thisco-registration allows calculation of the extracellular potentials fromthe applied electric field along the complex neural geometry. After theextracellular potentials are determined for each neural compartment as afunction of time during the applied stimulation, for each neuralposition relative to the electrode, the neuron/axon model 222 can beused to test whether the applied stimulus exceeded the neural thresholdthat triggers an action potential.

As another example, using the neuron/axon model 222 to simulate how theneurons (located as determined from the DTI-derived conductivity data,in one example) behave, the threshold value of the second difference ofelectric field that will result in such propagating action potentialscan be calculated. The stimulating influence of the electric field (asrepresented by the electric field model 220) is applied to theneuron/axon model neurons to define a threshold value. This thresholdvalue can then used to define the boundary of the design VTA in thenon-uniform conductivity tissue, similar to as discussed above withrespect to FIG. 4.

The electrode structure search 218 can vary the electrode height anddiameter over the range of predefined values, such as mentioned above.Corresponding design VTAs can be determined over the range of parametervalues. Those skilled in the art will appreciate that variousconstraints that can be programmed into the electrode structure search218 or into the parameterization space 202 to reduce computationalcomplexity of the design system. For example, it may be desirable toconstrain the diameter to height (aspect) ratio to remain below apredetermined value (e.g., d/h>1), which value further can varyaccording to the shape and volume of the target VTA 206. Those skilledin the art will appreciate various ways to quantify the shape and sizeof the target VTA 206 such that an appropriate VTA aspect ratio can beestablished to constrain the optimization accordingly.

The optimization method 214 can also include one or more scoringfunctions 226 that are employed to evaluate at least some of the designVTAs 216 in the search space relative to the target VTA 206. Differentsearch components of the optimization method can utilize the samescoring function or different scoring functions can be utilized fordifferent searches. As one example, each design VTA (corresponding to aniteration of the electrode structure search 218) can be scored accordingto the following equation:Score=(VTA_(in target)/VTA_(target))*(−VTA_(out target)/Xvolume),  Equation 3

where:

-   -   VTA_(in target) corresponds to the portion of the design VTA 216        that resides within the target VTA 206,    -   VTA_(out target) corresponds to the portion of the design VTA        216 that resides outside of the target VTA 206, and    -   Xvolume defines the penalty for stimulation spread outside of        the target VTA.        The highest scoring electrode design VTA will represent the        maximal volume overlap between the stimulation VTA and the        target VTA while providing a penalty for VTA spread outside of        the target VTA. In practice, variants of the above scoring        equation (as well as other scoring functions) can be used to        hone in on an appropriate value for the X volume parameter.

As part of the electrode structure search 218, one or more of theelectrode stimulation parameters 210 can be adjusted for the givenelectrode structure design so that the design VTA spreads to or near tothe edge of the target VTA 206. Alternatively, the electrode structuresearch 218 can iteratively adjust one or more electrode structureparameters while the electrode stimulation parameters remain constant,generating a new design VTA 216 for each iteration. Those skilled in theart will appreciate various approaches that can be utilized to generatedesign VTAs 216 over the entire or a subset of the parameterizationspace.

The results of the electrode structure search 218 can provide one ormore electrode designs 204. For example, the electrode structure search218 can provide a plurality of electrode designs (e.g., having definedelectrode structure and electrode stimulation parameters) that result inrespective design VTAs that best match the target VTA 206.

By way of illustration, FIGS. 11, 12 and 13 depict images 312, 314 and316, respectively, that include example design VTAs generated forelectrode contact 1 of a given electrode structure (e.g., as defined byelectrode structure parameters 208) 304 for different stimulationparameters. In FIGS. 11, 12 and 13, the same reference numbers are usedto refer to the same structural parts as introduced with respect to FIG.10. The VTAs generated at contact 1 result in some amount ofVTA_(in target) and some amount of VTA_(out target), both of which varyas a function of the stimulation parameter settings and the electrodecontact geometry. In FIG. 11 the image 312 includes a design VTA 320 fora stimulation voltage at contact 1 of about −2 V. In FIG. 12, the image314 includes a design VTA 322 for a stimulation voltage at contact 1 ofabout −2.5 V. In FIG. 13, the image 316 includes a design VTA 324 for astimulation voltage at contact 1 of about −3 V. In FIGS. 10, 11, 12 and13, for purposes of simplicity of explanation and for sake ofcomparison, it is assumed that the electrode geometry remains constant.By applying the above scoring criteria, the example of FIG. 12 has thehighest score and, thus, can be utilized to establish the electricalstimulation parameters 210 associated with the given set of electrodestructure parameters 208 for the electrode design of FIG. 9. It will beappreciated that more than three different stimulation parameters can beevaluated and scored as part of the electrode structure search 218.

Referring back to FIG. 9, it is again noted that the electrodelocation/trajectory parameters 212 can remain fixed during theoptimization of electrode design associated with the electrode structuresearch 218 and a contact spacing search 232 (when implemented). Thesurgical trajectory for electrode implantation in a given nucleus isrelatively standardized. As one example, a general trajectory for STNDBS approximately 65 degrees up from the axial plane and approximately10 degrees off the saggital plane. As another example, the generaltrajectory for GPi DBS can be approximately 70 degrees up from the axialplane and approximately 5 degrees off the saggital plane. The particulartrajectory used in an individual patient, however, is chosen based onpre-operative imaging data to avoid major blood vessels, sulci, and theventricles.

The electrode/location and trajectory parameters 212 thus can be set tostandard electrode trajectories for a given nucleus (adjusted to avoidmajor blood vessels, sulci, and the ventricles) with the contactlocation at the anatomical center of the nucleus. The parameter valuescan remain fixed during the electrode structure search 218, such asdescribed above. After a subset of one or more electrode designs hasbeen determined for the target VTA, the optimization method 214 can varyelectrode structure and stimulation parameters to accommodate surgicalvariability (e.g., associated with surgical placement of the electrode)and anatomical variability (e.g., associated with imaging techniques fordetermining anatomical and electrical models).

The optimization method 214 can also include a variability adjustmentcomponent 230. The adjustment component 230 can refine a portion of thesearch space to and reevaluate the efficacy of one or more electrodedesigns to account for variability that would be expected clinically.One source of clinical variability is the stereotactic accuracy of theelectrode placement. For example, it has been determined that thereexists approximately 1 mm of uncertainty in all directions in threedimensional space when implanting many types of electrodes, such as DBSelectrodes. Therefore, the variability adjustment component 230 canreevaluate the electrode structure parameters for each of a plurality ofbest-performing electrode contact designs 204, such as by adjusting theelectrode location/trajectory parameter 212 to reflect the uncertaintyin three-dimensional space.

As an example, a plurality (e.g., two or more, such as five) of the topscoring electrode contact designs 204 for the target VTA 206 can besubjected to further analysis. For example, the electrode location andtrajectory can be incrementally adjusted (e.g., relative to thegeometric center of the target VTA) in the dorsal/ventral,anterior/posterior, and medial/lateral directions) and the resultingdesign VTAs 216 can be scored according the sub-optimal electrodeplacements. The electrodes location parameters can be adjusted, forexample, in predetermined increments that are less than or equal to theamount of defined variation.

The surgical trajectory of the electrode in the 3D anatomical region canalso be varied, such as in a plurality of increments over a range (e.g.,+/−5 degrees) relative to the axial plane and in similar increments overa range (e.g., +/−5 degrees) relative to the saggital plane. Each of thefinalist DBS electrode contact designs 204 will thus be assigned aplurality of scores for each associated design VTAs 216 resulting fromthe incremental adjustments (to accommodate variation in location andtrajectory). The set of VTA scores for each respective electrode design204 being reevaluated can be aggregated to provide an aggregate totalscore for each design. The average VTA scores for each electrode design204 further can be averaged and the highest scoring electrode design canbe selected as representing an optimal DBS electrode contact for thegiven target nucleus. The same scoring function 226 can be utilized bythe variability adjustment component 230 as is used by the electrodestructure search 218. Alternatively, different scoring functions couldbe utilized, such as by applying weighting differently according tovariations in the electrode/trajectory parameters 212 differently (e.g.,imposing an increased penalty as the variations increase).

By way of example, existing neurostimulation devices are being equippedwith current steering capabilities (e.g., implantable pulse generatorshaving 8 or 16 independent current sources). The existence of currentsteering technology in neurostimulation becomes an attractive mode ofoperation in a situation where two (or more) contacts are located withinthe target VTA, but neither is in a position to adequately stimulate thetarget VTA without spreading stimulation into neighboring side effectregions. A possible solution would be to balance stimulation through thetwo contacts, possibly with unequal stimulus amplitudes, such that thetarget VTA is maximally stimulated.

The optimization method 214 can also employ a contact spacing search 232to define a contact spacing that further maximizes the design VTAcoverage with respect to the target VTA 206. Based on current steeringanalysis, there exists a contact spacing that maximizes VTA coveragealong the trajectory of the electrode shaft. The optimization method 214can employ the contact spacing search 232, such as in situations whenmore than one electrode contact will be activated to supply electricfields that may interact spatially and/or temporally. As one example,the optimization method 214 can activate the contact spacing search 232to evaluate the effects of current-steering, such as in situations whenthe top scoring electrode design fails to meet a minimum score relativeto the target VTA 206.

As one example, the contact spacing search 232 can search theparameterization space 202 according to spatially and/or temporallyoverlapping electric fields generated from multiple electrodes. Thecontact spacing search 232 can score the resulting design VTAs todetermine which design or set of electrode designs having multiplecontacts with independently controllable sources, best matches thetarget VTA. It should be noted that the electrode structure search 218can be implemented as part 8 of the contact spacing search 232. As aresult, the combination of electrode structure search 218 and thecontact spacing search 232 can be employed to identify a contact spacingin conjunction with other electrode structure parameters (e.g., heightand diameter for each contact) 208 that, height and diameter, willafford a maximal VTA coverage along the trajectory of the electrodeshaft.

Thus, the contact spacing search 232 can be utilized to adjust thespacing between one or more pairs of electrodes in the electrode design204 to determine spacing parameters for the electrode design thatprovides a design VTA 216 that more closely matches the target VTA 206.

The impact of electrode trajectory variability and electrode locationvariability can be evaluated with respect to the added VTA coverage thatcan be attained with current steering contacts. The contact spacingsearch 232 can result in the electric field model 220 representing twoor more electric field distributions, which can overlap according to thespacing and charge distribution of the respective fields. The spacingbetween electrode contacts can be defined in the parameterization space202 by appropriate spacing parameters in the electrode structureparameters 208. Those skilled in the art will understand ways toconstruct appropriate electric field model 220 for the multiple contactelectrode based on the teachings contained herein.

The variability adjustment 230 can also be utilized in conjunction withthe contact spacing search 232 and the resulting multi-contact electrodedesign 204, similar to as described with respect to the single contactmethodology. The variability adjustment component can thus identify atheoretically optimal trajectory that should be used with the determinedoptimal contact design and contact spacing (e.g., as defined by theelectrode structure parameters 208 of the resulting electrode design204).

In view of the foregoing, it will be appreciated that the design system200 thus can provide a nuclei-specific single contact electrode designor a multiple contact design that is customized to the anatomical andelectrical constraints of the target nucleus (e.g., the STN or GPi). Byalso accounting for the potential variability in electrode placement andtrajectory, such an electrode design should afford increase resilienceto surgical placement variability while also maximizing VTA coverage ofthe target VTA. As described herein, the resulting stimulationparameters for the electrode design can be employed to program an LPG orother stimulation device for applying stimulation to an electrodeconstructed according to the structural parameters, thereby achievingneurostimulation that substantially matches the target VTA.

By way of further illustration, FIGS. 14A, 14B and 14C depict theeffects of different electrode contact geometries on the design VTA. Theexample FIGS. 14A, 14B and 14C illustrate the VTA as contour plots forsecond difference threshold values (similar to FIG. 6). The scale thatdefines the second difference threshold is indicated above the figures(indicated at 398). Each contour plot depicts the VTA at four voltagevalues (e.g., −0.4 V, −0.6 V, −0.8 V, −1.0 V) for stimulation at 130 Hz.The plots in the respective figures also have be generated for aconstant surface area electrode contact geometry; although, as describedherein, the surface area of an electrode contacts need not (andtypically will not) remain constant when determining an electrode designfor a target VTA according to an aspect of the invention.

FIG. 14A demonstrates contour plots 400, 402 and 404 for seconddifference threshold values for an electrode contact geometry (e.g.,that can be characterized as tall and skinny) having a diameter of 0.5mm and a height of 3.81 mm. The plots 400, 402 and 404 each have adifferent pulse width, such as about 60 μsec, 90 μsec, and 210 μsec.FIG. 14B demonstrates contour plots 410, 412 and 414 for seconddifference threshold values for an electrode contact geometry having adiameter of 1.27 mm and a height of 1.5 mm. The plots 410, 412 and 414each have a different pulse width, such as about 60 μsec, 90 μsec, and210 μs (the same as in the other figures for sake of comparison). FIG.14C demonstrates contour plots 420, 422 and 424 for second differencethreshold values for an electrode contact geometry (e.g., that can becharacterized as short and fat) having a diameter of 2.0 mm and a heightof 0.475 mm. The plots 400, 402 and 404 each have a different pulsewidth, such as about 60 μsec, 90 μsec, and 210 μsec. Thus, the examplesin FIGS. 14A, 14B and 14C demonstrate that the VTA aspect ratio

To further demonstrate the effects of electrode contact geometry, canprovide a useful metric to quantity VTA shape and size. FIGS. 15 16 and17 illustrate different measures and relationships that characterize VTAshape and volume relative to electrode geometry based on the resultsshown in FIGS. 14A, 14B and 14C. The information portrayed in the FIGS.15, 16 and 17 demonstrates that VTA shape and volume can be modulated bysimply changing the electrode geometry. For example, FIG. 15 depicts agraph 450 that plots electrode dimensions (height and diameter) as afunction of VTA aspect ratio. The VTA aspect ratio is determined bydividing the VTA by the height for plot 452 and by the diameter for plot454. The graph 450 thus includes a plot 452 of height as a function ofVTA aspect ratio and a plot 454 of diameter as a function of the VTAaspect ratio.

FIG. 16 depicts a graph 460 of VTA volume plotted as a function ofelectrode height for each of the pulse widths from FIGS. 14A, 14B and14C, which plots are indicated at 462, 464 and 466. The plot 462represents the VTA volume as function of height for the 60 μsec, plot464 corresponds to the 90 μs pulse width, and plot 466 corresponds tothe 210 μs pulse width. From FIG. 16, it can be demonstrated that, for agiven set of electrode geometry, increases in electrode height cause asubstantially linear increase in VTA volume, and that the rate ofincrease is dependent on the pulse width.

FIG. 17 depicts a graph 470 of VTA volume plotted as a function ofelectrode diameter for each of the pulse widths from FIGS. 14A, 14B and14C, which plots are indicated at 472, 474 and 476. From the plots 472,474 and 476, it can be shown that increases in electrode contactdiameter cause a nonlinear (e.g., nonlinear) logarithmic decrease in VTAvolume, which amount of decrease is dependent on stimulation pulsewidth.

In view of the foregoing, it will be appreciated that additionalvariations in the VTA shape can be achieved by adjusting other designparameters, such as the number of contacts and spacing, the electricalstimulation parameters and the like. Those skilled in the art willappreciate that the methods and systems described herein can be employedto customize an electrode design to maximize VTA spread for a giventarget nucleus.

By way of further example, FIGS. 18, 19 and 20 demonstrate the effectsof electrode geometry on VTA for a particular nucleus, namely theventral intermediate nucleus of the thalamus (VIM) 478. In particular,FIG. 18 depicts an electrode 480 having a single contact 482 insertedinto the thalamus 484. In the example of FIG. 18 the electrode ispositioned at the anatomical center of the VIM 478. The VIM is a longnarrow nucleus measuring approximately 8 mm (dorsal-ventral) byapproximately 3 mm (anterior-posterior) by approximately 12 mm(medial-lateral).

FIG. 19 depicts a VTA 480 for an electrode 482 having first electrodedesign parameters. In the example of FIG. 19, the electrode 482 includesa contact 484 that corresponds to a standard electrode contact geometry(e.g., having a height of approximately 1.5 mm, diameter ofapproximately 1.27 mm, providing a surface area≈6 mm²), with stimulationsettings of −1 V and 90 μs pulse width at 130 Hz. The aspect ratio (d/h)of the electrode contact 484 is approximately 0.4. The electrode designof FIG. 19 produces the VTA 480 to fills approximately 26% of the VIM478 before spreading outside the target VTA defined by the VIM.

FIG. 20 depicts a VTA 490 for an electrode 492 having a second(customized) electrode design parameters, which are different from thoseof the electrode 482 of FIG. 19, such as may be determined according toan aspect of the invention. In the example of FIG. 20, the electrodeincludes a contact 494 that is also positioned at the anatomical centerof the VIM. The electrode contact 494 is designed with a diameter ofapproximately 0.75 mm and a height of approximately 2.54 mm height toprovide an aspect ratio of approximately 0.4, which more closely matchesthe aspect ratio of the VIM 478 than the example electrode in theexample of FIG. 19. For sake of comparison, the electrode contact 494has approximately the same contact surface area as the example of FIG.19 and depicts a corresponding design VTA 490 under the same stimulation(stimulation voltage of about −1 V and 90 μs pulse width). The design ofFIG. 20 conditions results in better stimulation of the VIM 478 byproducing a VTA that fills 33% of the volume, which is about a 28%increase compared to the VTA 480 in the example of FIG. 19.Additionally, the custom electrode design 492 can result inapproximately 7% more stimulation of the VIM 478 with no increase inspread outside the boundary of the target VTA defined by the VIM.

What have been described above are examples or embodiments of theinvention. It is, of course, not possible to describe every conceivablecombination of components or methodologies for purposes of describingthe present invention, but one of ordinary skill in the art willrecognize that many further combinations and permutations of the presentinvention are possible. Accordingly, the invention is intended toembrace all such alterations, modifications and variations that fallwithin the invention claimed herein. In the claims, unless otherwiseindicated, the article “a” refers to “one or more than one”.

1. A method for determining an electrode design, comprising: selectingan anatomical region to achieve a desired therapeutic effect; defining atarget volume of tissue activation in the selected anatomical regionexpected to achieve the desired therapeutic effect; determining at leastone electrode structure parameter and at least one stimulation parameterthat provides a design volume of tissue activation that substantiallymatches the target volume of tissue activation; storing the determinedat least one electrode structure parameter and the at least onestimulation parameter to define the electrode design.
 2. The method ofclaim 1, wherein the at least one electrode structure parametercomprises dimensions for at least one contact of the electrode design.3. The method of claim 2, wherein the dimensions for the at least onecontact further comprise a dimension along a longitudinal axis and across-sectional dimension.
 4. The method of claim 1, wherein a parametersearch space is provided that includes a plurality of electrodestructure parameters and a plurality of stimulation parameters, thedetermination further comprising: searching through the parameter searchspace to ascertain which combination of the plurality of electrodestructure parameters and a plurality of stimulation parameters producesan electrode design expected to substantially match the target volume oftissue activation.
 5. The method of claim 4 further comprising:selecting a subset of plural electrode designs expected to substantiallymatch the target volume of tissue activation; characterizing changes inthe design volume of tissue activation for each electrode design in theselected subset according to changes in at least one of contact locationparameter and electrode trajectory parameter; and identifying whichelectrode design in the selected subset exhibits increased resilience,relative to other electrode designs, to the changes in at least one ofcontact location parameter and electrode trajectory parameter.
 6. Themethod of claim 1 wherein the at least one structural parametercomprises an aspect ratio defined by a ratio of a diameter and a lengthof the contact dimensions.
 7. The method of claim 1, wherein theelectrode design comprises a plurality of contacts spaced apart fromeach other along a longitudinal axis, the at least one structuralparameter further comprising a relative spacing between at least two ofthe plurality of contacts along the longitudinal axis.
 8. The method ofclaim 1, further comprising generating a score for the design volume oftissue activation to characterize an amount of overlap between thedesign volume of tissue activation and the target volume of tissueactivation.
 9. The method of claim 8, wherein the scoring furthercomprising applying a penalty to the score according to a spread of thedesign volume of tissue activation that extends outside the boundary ofthe target volume of tissue activation.
 10. The method of claim 1,wherein the determination of the design volume tissue activation furthercomprises predicting effects of neural stimulation, according to the atleast one electrode structure parameter and at least one stimulationparameter, for the anatomical region based on at least one thresholdthat characterizes an activation potential for the anatomical region inresponse to electrical stimulation.
 11. The method of claim 1, whereinthe defined target volume of tissue activation comprises a probabilisticdefinition that represents the anatomical region expected to achieve thedesired therapeutic effect.